I'll create a comprehensive README for your LocalStack Pro project:

This project demonstrates how to develop and test AWS applications locally using LocalStack Pro. It provides a simple workflow to upload and retrieve CSV files from an emulated S3 bucket, avoiding the costs and delays of working with the real AWS cloud.

• Local AWS S3 emulation using LocalStack Pro
• Command-line tools for uploading and downloading CSV files
• Environment-based configuration for easy switching between environments
• Clean project structure following Python best practices

• Python 3.12 or higher
• Docker and Docker Compose
• LocalStack Pro subscription (and authentication token)
• Poetry (for dependency management)

1. Clone this repository:

   git clone https://github.com/yourusername/localstack-pro-project.git
   cd localstack-pro-project

2. Set up Python environment with Poetry:

   poetry install

3. Create a .env file in the project root with your configuration:

   LOCALSTACK_ENDPOINT=http://localhost:4566
   LOCALSTACK_AUTH_TOKEN=your_localstack_pro_token
   AWS_ACCESS_KEY_ID=test
   AWS_SECRET_ACCESS_KEY=test
   AWS_REGION=us-east-1
   S3_BUCKET_NAME=todo-list-bucket
   S3_DEFAULT_KEY=todo-list.csv
   CSV_FILE_PATH=./data/sample-tasks.csv

4. Start LocalStack Pro using Docker Compose:

   docker compose up -d localstack

Initialize the S3 bucket in LocalStack:

poetry run setup-localstack

Upload a todo list CSV file to the S3 bucket:

poetry run upload-todo

You can also specify a different CSV file:

poetry run upload-todo /path/to/your/file.csv

Download and display the todo list from S3:

poetry run read-todo

localstack-pro-project/
├── .env                  # Environment variables (create this)
├── .gitignore            # Git ignore file
├── data/                 # Sample data files
│   └── sample-tasks.csv  # Example todo list
├── pyproject.toml        # Poetry configuration
├── README.md             # This file
├── src/                  # Source code
│   └── localstack_pro_project/
│       ├── __init__.py
│       ├── downloader.py # Download CSV from S3
│       ├── setup_localstack.py # Set up LocalStack
│       └── uploader.py   # Upload CSV to S3
└── tests/                # Test files

poetry add package-name

poetry run pytest

This project demonstrates the local-first development workflow described in "The Local Cloud Revolution: Rethinking AWS Development Workflows" chapter:

1. We use LocalStack Pro to emulate AWS S3 on your machine
2. The setup_localstack.py script creates the necessary S3 bucket
3. The uploader.py script pushes a CSV file to the emulated S3 bucket
4. The downloader.py script retrieves and displays the CSV data

This workflow provides instant feedback, costs nothing to run, and allows risk-free experimentation with AWS services.

• "Bucket already exists" error: This is normal if you've already created the bucket. The script handles this gracefully.
• Connection issues: Ensure LocalStack is running with docker ps. The container should be up and the 4566 port should be exposed.
• Authentication errors: Check that your LOCALSTACK_AUTH_TOKEN is correctly set in the .env file.

This project is licensed under the MIT License - see the LICENSE file for details.

• LocalStack team for providing the local AWS emulation
• AWS for their comprehensive cloud services and SDKs
• Docker and Docker Compose for making development simple and efficient